Comparison of the kinetic parameters estimated with LLSQ and NLSQ methods in DCE-MRI

線性與非線性最小平方法評估動態對比增強磁共振影像之動力學參數的比較

柯青僑(Cing-Ciao Ke)

指導教授 ： 王福年

國立清華大學/原子科學院/生醫工程與環境科學系/碩士(2011年)

https://doi.org/10.6843/NTHU.2011.00285

摘要

態對比增強磁共振影像技術在評估腫瘤特性中扮演著重要的角色，利用一些動力學參數，例如體積轉移常數和速率常數，可以達到定量的分析。為了獲得這些動力學參數，研究者通常利用非線性最小平方法擬合時間濃度曲線到動力學模型上。然而此方法是十分耗時的。先前的研究證明，對於修改後的Tofts and Kermode 模型，線性最小平方法可能是更準確且快速的方法。本研究我們利用電腦模擬評估線性最小平方法和非線性最小平方法在解Tofts and Kermode時動力學參數的正確性。此外我們也使用這兩種方法分析八個有腦腫瘤的病人數據。當訊雜比較低時，利用線性最小平方方法得到的參數將會比非線性最小平方方法準確。比起非線性最小平方法，利用線性最小平方法得到的參數的準確性和精密度較不易受體積轉移和速率常數變動影響。此外線性最小平方法的計算速度比非線性最小平方法快約十七倍。在實際臨床應用時，對於四個多形惡性神經膠質瘤的病人，線性最小平方法和非線性最小平方法在評估動力學參數上有顯著的差異。

關鍵字

動態對比增強磁共振影像技術 ； 體積轉移常數 ； 數率常數 ； 線性最小平方法 ； 非線性最小平方法

並列摘要

Dynamic contrast enhanced (DCE) MRI plays an important role for quantitative assessment of tumor characterization using the kinetic parameters, such as volume transfer constant (Ktrans) and rate constant (kep). Nonlinear least square (NLSQ) method is often used to fit concentration time curves to kinetics models for obtaining kinetic parameters. However, one disadvantage of this method is time-consuming. The previous study demonstrated that liner least-squares (LLSQ) method may be a more accurate and fast method than NLSQ method in solving modified Tofts and Kermode model. In this study, we performed computer simulations to assess the accuracy of estimated the kinetic parameters for LLSQ and NLSQ methods in solving Tofts and Kermode model. In addition, the two methods were used to analyze the data from eight patients with brain tumors. At lower signal-to-noise (SNR), the accuracy of parameters estimated with LLSQ method was better than NLSQ method. Compare with NLSQ method, effect of varying Ktrans and kep on accuracy and precision of the kinetic parameters with LLSQ method was smaller. Besides, the calculation velocity of LLSQ method was seventeen times faster than NLSQ method. In clinical application, there were significant differences between LLSQ and NLSQ estimated kinetic parameters on the all patients with glioblastoma multiforme (GBM).

並列關鍵字

dynamic contrast enhanced MRI ； volume transfer constant ； rate constant ； liner least-squares method ； nonlinear least-squares method

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